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Yonghao Xu

Assistant Professor

Linköping University

Sweden

Research Interests

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Professors in Sweden Professors in Artificial Intelligence Artificial Intelligence professors in Sweden

About

Yonghao Xu is an Assistant Professor at Linköping University in Sweden. His research focuses on advanced methodologies in remote sensing and artificial intelligence, as evidenced by his recent articles on topics such as causal fire spread modeling, adversarial defense in hyperspectral image classification, and the transformative impact of AI on urban sensing and imaging. Dr. Xu's work addresses critical challenges in AI security and geoscience, contributing to the development of innovative solutions in these fields.

Articles (17)

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2025

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2024

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2024

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2022

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2022

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2022

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2022

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2022

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2022

Collaborators (8)

Weikang Yu

Technical University of Munich

GERMANY

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Peter Atkinson

University of Lancaster

UNITED KINGDOM

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Zhiwei Li

Research Assistant Professor

Institute of Science and Technology

SOUTH KOREA

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Qiming Zheng

Assistant Professor

The Chinese University of Hong Kong (CUHK)

CHINA

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Marco Kuhlmann

Professor

Linköping University

SWEDEN

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Michael Schmitt

Professor

Bundeswehr University Munich

GERMANY

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Michael Felsberg

Professor

Linköping University

SWEDEN

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Peifeng Ma

Associate Professor

The Chinese University of Hong Kong (CUHK)

HONG KONG

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Yonghao Xu

Research Interests

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About

Articles (17)

Causal Xwildfire: Causality-instilled fire spread modelling for extreme events

Flexible Distribution Alignment: Towards Long-Tailed Semi-supervised Learning with Proper Calibration

Stealthy Adversarial Examples for Semantic Segmentation in Remote Sensing

S³ANet: Spatial–Spectral Self-Attention Learning Network for Defending Against Adversarial Attacks in Hyperspectral Image Classification

How will ai transform urban observing, sensing, imaging, and mapping?

Universal adversarial defense in remote sensing based on pre-trained denoising diffusion models

AI Security for Geoscience and Remote Sensing: Challenges and future trends

Backdoor Attacks for Remote Sensing Data With Wavelet Transform

Can Spectral Information Work While Extracting Spatial Distribution?—An Online Spectral Information Compensation Network for HSI Classification

There Are No Data Like More Data: Datasets for deep learning in Earth observation

Txt2Img-MHN: Remote Sensing Image Generation From Text Using Modern Hopfield Networks

Consistency-Regularized Region-Growing Network for Semantic Segmentation of Urban Scenes With Point-Level Annotations

Fine-Grained Classification of Urban Functional Zones and Landscape Pattern Analysis Using Hyperspectral Satellite Imagery: A Case Study of Wuhan

Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection

Robust Self-Ensembling Network for Hyperspectral Image Classification

Self-Ensembling GAN for Cross-Domain Semantic Segmentation

The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection From Multisource Satellite Imagery

Collaborators (8)

Weikang Yu

Peter Atkinson

Zhiwei Li

Qiming Zheng

Marco Kuhlmann

Michael Schmitt

Michael Felsberg

Peifeng Ma

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